Published May 19, 2025 | Version 2.0.0

Data used in SeuratIntegrate paper

  • 1. ROR icon Institut de Biochimie et Génétique Cellulaires
  • 2. ROR icon Centre National de la Recherche Scientifique
  • 3. Université de Bordeaux
  • 1. ROR icon Centre National de la Recherche Scientifique
  • 2. ROR icon Institut de Biochimie et Génétique Cellulaires
  • 3. Université de Bordeaux

Description

This repository gathers the data and code used to generate hepatocellular carcinoma analyses in the paper presenting SeuratIntegrate. It contains the scripts to reproduce the figures presented in the article. Some figures are also available as pdf files.

To be able to fully reproduce the results from the paper, one shoud:

  • download all the files
  • install R 4.3.3, with correspondig base R packages (stats, graphics, grDevices, utils, datasets, methods and base)
  • install R packages listed in the file sessionInfo.txt
  • install the provided version of SeuratIntegrate. In an R session, run:
remotes::install_local("path/to/SeuratIntegrate_0.4.1.tar.gz")
  • install (mini)conda if necessary (we used miniconda version 23.11.0)
  • install the conda environments (if it fails with the *package-list.yml files, use the *package-list-from-history.yml files instead):
conda env create --file SeuratIntegrate_bbknn_package-list.yml
conda env create --file SeuratIntegrate_scanorama_package-list.yml
conda env create --file SeuratIntegrate_scvi-tools_package-list.yml
conda env create --file SeuratIntegrate_trvae_package-list.yml
  • open an R session to make the conda environments usable by SeuratIntegrate:
library(SeuratIntegrate)

UpdateEnvCache("bbknn", conda.env = "SeuratIntegrate_bbknn", conda.env.is.path = FALSE)
UpdateEnvCache("scanorama", conda.env = "SeuratIntegrate_scanorama", conda.env.is.path = FALSE)
UpdateEnvCache("scvi", conda.env = "SeuratIntegrate_scvi-tools", conda.env.is.path = FALSE)
UpdateEnvCache("trvae", conda.env = "SeuratIntegrate_trvae", conda.env.is.path = FALSE)

 

Once done, running the code in integrate.R should produce reproducible results. Note that lines 3 to 6 from integrate.R should be adapted to the user's setup.
integrate.R is subdivided into six main parts:

  1. Preparation: lines 1-56
  2. Preprocessing: lines 58-74
  3. Integration: lines 76-121
  4. Processing of integration outputs: lines 126-267
  5. Scoring of integration outputs: lines 269-353
  6. Plotting: lines 380-507

Intermediate SeuratObjects have been saved between steps 3 and 4 and 5 and 6 (liver10k_integrated_object.RDS and liver10k_integrated_scored_object.RDS respectively). It is possible to start with these intermediate SeuratObjects to avoid the preceding steps, given that the Preparation step is always run before. 

Files

scores_rank_rescale_manual_celltype_v2.pdf

Files (2.3 GB)

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Additional details

Funding

Agence Nationale de la Recherche
EMTSens - Electrophysiologic, Morphologic and Trancriptomic plasticity in spinal dorsal horn Inhibitory networks to decipher atypical sensory perception. ANR-21-CE16-0040
Institut National du Cancer
Exploiting immunity of hepatocellular carcinoma to improve the treatment of patients 251534

Software

Repository URL
https://github.com/cbib/Seurat-Integrate
Programming language
R
Development Status
Active